AI Research Scientist

Primary Responsibilities

• Perform research, assessments, and technical evaluations of AI models, methods, and frameworks to solve problems or derive benefits to company AI capabilities and generative AI program

• Conduct feasibility studies and create working proof of concepts for use-cases by exploring applications of AI to internal problems and datasets to de-risk AI engineering delivery

• Lead delivery of smaller projects – understand the problem, propose technology solution, and align with stakeholders on expected results outcomes

• Participate in internal professional communities of practice and mentor colleagues to raise artificial intelligence and data science maturity within the company

• Assist in technical training to up-skill colleagues to raise the data science competency levels within the company

• Proactively scan and keep up to date with AI research

Requirements

• Bachelor's, Master's or PhD in Artificial Intelligence, Machine Learning, Computer Science, Computer Vision, Image processing highly preferred

• We evaluate candidates on a case-by case basis but appreciate qualifications in quantitative, scientific and technology disciplines such as Mathematics, Statistics, Data Science, Analytics, Physics, and Bioinformatics

• We seek candidates that combine technical depth with the ability to work collaboratively and create impact

• Relevant working experience in fields related to artificial intelligence, machine learning, data science

• Understanding of artificial intelligence research landscape and ability to review research publications, particularly in one of the following fields: generative AI, Machine Learning (ML), Natural Language Processing (NLP), or Computer Vision (CV)

• Hands-on code development experience and familiarity with the Python scientific computing stacks

• Ability to communicate and express technical viewpoints to senior stakeholders with succinctness and clarity

• Proficiency in GenAI, deep learning, NLP, CV, and ML frameworks, other AI disciplines regarded useful

• Familiarity with developing and deploying within a cloud-based infrastructure and services (AWS or MS Azure environment) is plus

• Domain knowledge in pharmaceutical business areas such as research, clinical, manufacturing, or commercial is plus